Pronounced warming and wetting of climate in the Qilian Mountains during 1961–2022

Abstract

Accurate high-resolution datasets on regional climate change are vital for ecological assessments, yet it remains difficult to obtain the spatiotemporal dynamics of air temperature and precipitation in high-elevation mountainous regions due to complex topography. Existing gridded climate datasets are often too coarse to represent the strong spatial heterogeneity of mountainous regions. To address this knowledge gap, downscaled air temperature and precipitation datasets provide an effective way to generate high precision climate data. Here, we downscaled the CN05.1 dataset using a geographically weighted regression model to produce a 1 km × 1 km monthly air temperature and precipitation dataset for the Qilian Mountains during 1961–2022. The downscaled air temperature and precipitation were validated using observations from high-elevation meteorological stations. Compared with the original CN05.1 product, the downscaled dataset showed better agreement with station observations and captured finer terrain-driven patterns. Results indicated the high-resolution data reveal mean annual air temperature and precipitation increased significantly, with strongest warming in winter and the most marked precipitation increased in summer and winter. Spatially, the strongest warming trend was observed in the Qaidam Basin, whereas the most pronounced wetting occurred in the Qinghai Lake Basin. Importantly, regions with elevations >4500 experienced the fastest rate of warming than lower regions. These findings improve our understanding of historical climate change in the Qilian Mountains and provide a high-resolution climate dataset suitable for mountain-scale ecological applications.